library(tidyverse)
library(ggtext)
cols <- c("region", "chr", "midPos", "Nsites", "Fst")
matxgrt_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/MAT--x--GRT--size-50000--step-10000.tsv",
skip = 2,
delim = "\t",
col_names = cols,
show_col_types = FALSE)
matxgrt_data_cum <- matxgrt_data %>%
group_by(chr) %>%
summarise(max_pos = max(midPos)) %>%
mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
select(chr, pos_add)
matxgrt_data <- matxgrt_data %>%
inner_join(matxgrt_data_cum, by = "chr") %>%
mutate(pos_cum = midPos + pos_add)
matxgrt_axis_set <- matxgrt_data %>%
group_by(chr) %>%
summarise(center = mean(pos_cum))
matxgrt_plot <- ggplot(data = matxgrt_data,
mapping = aes(x = pos_cum,
y = Fst,
color = as_factor(chr))) +
geom_point(alpha = 0.75, size = 0.5) +
geom_hline(yintercept = mean(matxgrt_data$Fst)) +
geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_x_continuous(label = matxgrt_axis_set$chr,
breaks = matxgrt_axis_set$center) +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
scale_color_manual(values = rep(c("darkslateblue", "thistle"),
unique(length(matxgrt_axis_set$chr)))) +
labs(x = NULL,
y = "Fst",
title = "MAT--x--GRT--size-50000--step-10000") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
matxgrt_plot

matxgrt_chr2_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000002.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(matxgrt_data$Fst)) +
geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "MAT--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 2 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
matxgrt_chr2_plot

matxgrt_chr2_elev_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(matxgrt_data$Fst)) +
geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "MAT--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 2 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
matxgrt_chr2_elev_plot

matxgrt_chr3_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000003.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(matxgrt_data$Fst)) +
geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "MAT--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 3 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
matxgrt_chr3_plot

matxgrt_chr3_elev_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(matxgrt_data$Fst)) +
geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "MAT--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 3 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
matxgrt_chr3_elev_plot

canxgrt_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/CAN--x--GRT--size-50000--step-10000.tsv",
skip = 2,
delim = "\t",
col_names = cols,
show_col_types = FALSE)
canxgrt_data_cum <- canxgrt_data %>%
group_by(chr) %>%
summarise(max_pos = max(midPos)) %>%
mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
select(chr, pos_add)
canxgrt_data <- canxgrt_data %>%
inner_join(canxgrt_data_cum, by = "chr") %>%
mutate(pos_cum = midPos + pos_add)
canxgrt_axis_set <- canxgrt_data %>%
group_by(chr) %>%
summarise(center = mean(pos_cum))
canxgrt_plot <- ggplot(data = canxgrt_data,
mapping = aes(x = pos_cum,
y = Fst,
color = as_factor(chr))) +
geom_point(alpha = 0.75, size = 0.5) +
geom_hline(yintercept = mean(canxgrt_data$Fst)) +
geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_x_continuous(label = canxgrt_axis_set$chr,
breaks = canxgrt_axis_set$center) +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
scale_color_manual(values = rep(c("darkslateblue", "thistle"),
unique(length(canxgrt_axis_set$chr)))) +
labs(x = NULL,
y = "Fst",
title = "CAN--x--GRT--size-50000--step-10000") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxgrt_plot

canxgrt_chr2_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000002.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxgrt_data$Fst)) +
geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 2 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxgrt_chr2_plot

canxgrt_chr2_elev_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxgrt_data$Fst)) +
geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 2 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxgrt_chr2_elev_plot

canxgrt_chr3_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000003.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxgrt_data$Fst)) +
geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 3 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxgrt_chr3_plot

canxgrt_chr3_elev_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxgrt_data$Fst)) +
geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--GRT--size-50000--step-1000",
subtitle = "Chromosome 3 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxgrt_chr3_elev_plot

canxmat_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/CAN--x--MAT--size-50000--step-10000.tsv",
skip = 2,
delim = "\t",
col_names = cols,
show_col_types = FALSE)
canxmat_data_cum <- canxmat_data %>%
group_by(chr) %>%
summarise(max_pos = max(midPos)) %>%
mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
select(chr, pos_add)
canxmat_data <- canxmat_data %>%
inner_join(canxmat_data_cum, by = "chr") %>%
mutate(pos_cum = midPos + pos_add)
canxmat_axis_set <- canxmat_data %>%
group_by(chr) %>%
summarise(center = mean(pos_cum))
canxmat_plot <- ggplot(data = canxmat_data,
mapping = aes(x = pos_cum,
y = Fst,
color = as_factor(chr))) +
geom_point(alpha = 0.75, size = 0.5) +
geom_hline(yintercept = mean(canxmat_data$Fst)) +
geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_x_continuous(label = canxmat_axis_set$chr,
breaks = canxmat_axis_set$center) +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
scale_color_manual(values = rep(c("darkslateblue", "thistle"),
unique(length(canxmat_axis_set$chr)))) +
labs(x = NULL,
y = "Fst",
title = "CAN--x--MAT--size-50000--step-10000") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxmat_plot

canxmat_chr2_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000002.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxmat_data$Fst)) +
geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--MAT--size-50000--step-1000",
subtitle = "Chromosome 2 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxmat_chr2_plot

canxmat_chr2_elev_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxmat_data$Fst)) +
geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--MAT--size-50000--step-1000",
subtitle = "Chromosome 2 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxmat_chr2_elev_plot

canxmat_chr3_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000003.1"),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxmat_data$Fst)) +
geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--MAT--size-50000--step-1000",
subtitle = "Chromosome 3 YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxmat_chr3_plot

canxmat_chr3_elev_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000),
mapping = aes(x = midPos,
y = Fst)) +
geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
geom_hline(yintercept = mean(canxmat_data$Fst)) +
geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)),
linetype = "dashed",
colour = "red") +
scale_y_continuous(expand = c(0,0),
limits = c(-0.05, 1)) +
labs(x = "Mid-Window Position",
y = "Fst",
title = "CAN--x--MAT--size-50000--step-1000",
subtitle = "Chromosome 3 elevated YU_APseudo genome") +
theme_bw() +
theme(legend.position = "none",
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
axis.title.y = element_markdown(),
axis.text.x = element_text(angle = 90,
size = 8,
vjust = 0.5))
canxmat_chr3_elev_plot

---
title: "Sliding Windows"
output: html_notebook
---


```{r packages}
library(tidyverse)
library(ggtext)
```


```{r matxgrt}
cols <- c("region", "chr", "midPos", "Nsites", "Fst")

matxgrt_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/MAT--x--GRT--size-50000--step-10000.tsv", 
                           skip = 2, 
                           delim = "\t", 
                           col_names = cols, 
                           show_col_types = FALSE)

matxgrt_data_cum <- matxgrt_data %>%
  group_by(chr) %>%
  summarise(max_pos = max(midPos)) %>%
  mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
  select(chr, pos_add)

matxgrt_data <- matxgrt_data %>% 
  inner_join(matxgrt_data_cum, by = "chr") %>%
  mutate(pos_cum = midPos + pos_add)

matxgrt_axis_set <- matxgrt_data %>%
  group_by(chr) %>%
  summarise(center = mean(pos_cum))

matxgrt_plot <- ggplot(data = matxgrt_data, 
                       mapping = aes(x = pos_cum,
                                     y = Fst, 
                                     color = as_factor(chr))) +
  geom_point(alpha = 0.75, size = 0.5) +
  geom_hline(yintercept = mean(matxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_x_continuous(label = matxgrt_axis_set$chr, 
                     breaks = matxgrt_axis_set$center) +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  scale_color_manual(values = rep(c("darkslateblue", "thistle"), 
                                  unique(length(matxgrt_axis_set$chr)))) +
  labs(x = NULL, 
       y = "Fst", 
       title = "MAT--x--GRT--size-50000--step-10000") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
matxgrt_plot

matxgrt_chr2_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000002.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(matxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "MAT--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 2 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
matxgrt_chr2_plot

matxgrt_chr2_elev_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(matxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "MAT--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 2 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
matxgrt_chr2_elev_plot

matxgrt_chr3_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000003.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(matxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "MAT--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 3 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
matxgrt_chr3_plot

matxgrt_chr3_elev_plot <- ggplot(data = filter(matxgrt_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(matxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(matxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "MAT--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 3 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
matxgrt_chr3_elev_plot
```

```{r canxgrt}
canxgrt_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/CAN--x--GRT--size-50000--step-10000.tsv", 
                           skip = 2, 
                           delim = "\t", 
                           col_names = cols, 
                           show_col_types = FALSE)

canxgrt_data_cum <- canxgrt_data %>%
  group_by(chr) %>%
  summarise(max_pos = max(midPos)) %>%
  mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
  select(chr, pos_add)

canxgrt_data <- canxgrt_data %>% 
  inner_join(canxgrt_data_cum, by = "chr") %>%
  mutate(pos_cum = midPos + pos_add)

canxgrt_axis_set <- canxgrt_data %>%
  group_by(chr) %>%
  summarise(center = mean(pos_cum))

canxgrt_plot <- ggplot(data = canxgrt_data, 
                       mapping = aes(x = pos_cum,
                                     y = Fst, 
                                     color = as_factor(chr))) +
  geom_point(alpha = 0.75, size = 0.5) +
  geom_hline(yintercept = mean(canxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_x_continuous(label = canxgrt_axis_set$chr, 
                     breaks = canxgrt_axis_set$center) +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  scale_color_manual(values = rep(c("darkslateblue", "thistle"), 
                                  unique(length(canxgrt_axis_set$chr)))) +
  labs(x = NULL, 
       y = "Fst", 
       title = "CAN--x--GRT--size-50000--step-10000") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxgrt_plot

canxgrt_chr2_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000002.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 2 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxgrt_chr2_plot

canxgrt_chr2_elev_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 2 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxgrt_chr2_elev_plot

canxgrt_chr3_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000003.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 3 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxgrt_chr3_plot

canxgrt_chr3_elev_plot <- ggplot(data = filter(canxgrt_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxgrt_data$Fst)) +
  geom_hline(yintercept = quantile(canxgrt_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--GRT--size-50000--step-1000", 
       subtitle = "Chromosome 3 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxgrt_chr3_elev_plot
```

```{r canxmat}
canxmat_data <- read_delim("data/pw_fst/sliding_window_fst-4ind-pop-size/CAN--x--MAT--size-50000--step-10000.tsv", 
                           skip = 2, 
                           delim = "\t", 
                           col_names = cols, 
                           show_col_types = FALSE)

canxmat_data_cum <- canxmat_data %>%
  group_by(chr) %>%
  summarise(max_pos = max(midPos)) %>%
  mutate(pos_add = lag(cumsum(max_pos), default = 0)) %>%
  select(chr, pos_add)

canxmat_data <- canxmat_data %>% 
  inner_join(canxmat_data_cum, by = "chr") %>%
  mutate(pos_cum = midPos + pos_add)

canxmat_axis_set <- canxmat_data %>%
  group_by(chr) %>%
  summarise(center = mean(pos_cum))

canxmat_plot <- ggplot(data = canxmat_data, 
                       mapping = aes(x = pos_cum,
                                     y = Fst, 
                                     color = as_factor(chr))) +
  geom_point(alpha = 0.75, size = 0.5) +
  geom_hline(yintercept = mean(canxmat_data$Fst)) +
  geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_x_continuous(label = canxmat_axis_set$chr, 
                     breaks = canxmat_axis_set$center) +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  scale_color_manual(values = rep(c("darkslateblue", "thistle"), 
                                  unique(length(canxmat_axis_set$chr)))) +
  labs(x = NULL, 
       y = "Fst", 
       title = "CAN--x--MAT--size-50000--step-10000") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxmat_plot

canxmat_chr2_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000002.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxmat_data$Fst)) +
  geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--MAT--size-50000--step-1000", 
       subtitle = "Chromosome 2 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxmat_chr2_plot

canxmat_chr2_elev_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000002.1" & midPos >= 50000000 & midPos <= 53000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxmat_data$Fst)) +
  geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--MAT--size-50000--step-1000", 
       subtitle = "Chromosome 2 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxmat_chr2_elev_plot

canxmat_chr3_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000003.1"), 
                            mapping = aes(x = midPos, 
                                          y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxmat_data$Fst)) +
  geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--MAT--size-50000--step-1000", 
       subtitle = "Chromosome 3 YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxmat_chr3_plot

canxmat_chr3_elev_plot <- ggplot(data = filter(canxmat_data, chr == "JBGGWU010000003.1" & midPos >= 29000000 & midPos <= 32000000), 
                                 mapping = aes(x = midPos, 
                                               y = Fst)) +
  geom_point(alpha = 0.75, size = 0.5, color = "darkslateblue") +
  geom_hline(yintercept = mean(canxmat_data$Fst)) +
  geom_hline(yintercept = quantile(canxmat_data$Fst, probs = c(0.99)), 
             linetype = "dashed", 
             colour = "red") +
  scale_y_continuous(expand = c(0,0), 
                     limits = c(-0.05, 1)) +
  labs(x = "Mid-Window Position", 
       y = "Fst", 
       title = "CAN--x--MAT--size-50000--step-1000", 
       subtitle = "Chromosome 3 elevated YU_APseudo genome") +
  theme_bw() +
  theme(legend.position = "none", 
        panel.grid.major.x = element_blank(), 
        panel.grid.minor.x = element_blank(), 
        axis.title.y = element_markdown(), 
        axis.text.x = element_text(angle = 90, 
                                   size = 8, 
                                   vjust = 0.5))
canxmat_chr3_elev_plot
```



